About the CourseThis one-week intensive course teaches current approaches in the statistical and computational analysis of large-scale experiments in biology. The course focus on the methods for downstream analysis of high-throughput sequencing experiments, including DNA sequencing (variant calling), RNA sequencing (differential expression), QTL analysis, epigenetics. Lectures also cover essentials including statistical testing, machine learning, visualisation and bioinformatic metadata integration. The course is intended for researchers who have a basic familiarity with the experimental technologies and the biology of the genome. The four practical sessions of the course will require simple programming in the language R; introductory and advanced language tutorials will be provided.
- Introduction to R and Bioconductor
- Elements of statistics: hypothesis testing, machine learning, visualisation
- Statistics for differential expression
- Computing with sequences and genomic intervals
- RNA-Seq data analysis
- DNA Variant calling
- Aspects of epigenetics
- Annotation of genes, genomic features and variants
- Gene set enrichment analysis
Course StructureThe course consists of
- morning lectures: 20 x 45 minutes: Monday to Friday 8:30am - 12:00am
- 4 practical computer tutorials in the afternoons (2pm - 5pm) on Monday, Tuesday, Thursday and Friday
- 4 flashlight sessions (5pm to 5:30pm) on Monday, Tuesday, Thursday and Friday
Course ProgramClick here to view the agenda or download the agenda
The course material will be available in electronic form during the course.
Computer TutorialsThe labs will be worked on in groups with expert guidance (all lecturers from the morning sessions plus teaching assistants).
Participants are required to bring their own laptops with the most recent release versions of R and Bioconductor installed. A WiFi network card is welcome to connect to our local network - however, no connections to the internet will be possible from the WLAN at the course venue.